Levi Rauchwerger

Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs

We analyze the universality and generalization of graph neural networks (GNNs) on attributed graphs, i.e., with node attributes. To this end, we propose pseudometrics over the space of all attributed graphs that describe the fine-grained expressivity of GNNs. Namely, GNNs are both Lipschitz continuo…